Using word embedding to extend words for searching POI names
I think word embeddings are overkill in this particular case.

My suggestion would be to go for a simple dictionary based approach: compose sets of semantically related words, and then use those to expand your query terms. This might take a bit longer to set up, but has several advantages:


simplicity: you can't make many mistakes with this
transparency: you know exactly why a certain term matches, and another one doesn't
accuracy: you have tight control over the whole process; if some term is wrong, you remove it from the set. You cannot do that with embeddings
resources: a dictionary-based approach is far simpler and needs less storage


'Old tech' doesn't sound as sexy as the latest deep learning stuff, but unless you want to have this as a toy project to learn about how to do things with embeddings I would say the latter are the wrong tool for the job. At least you can be sure that it works, and if it doesn't you can easily fix it.